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An agent-based spatiotemporal integrated approach to simulating in-home water and related energy use behaviour: A test case of Beijing, China

机译:基于Agent的时空综合方法模拟室内用水和相关能源的使用行为:中国北京的一个测试案例

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摘要

Water and energy consumptions in the residential sector are highly correlated. A better understanding of the correlation would help save both water and energy, for example, through technological innovations, management and policies. Recently, there is an increasing need for a higher spatiotemporal resolution in the analysis and modelling of water-energy demand, as the results would be more useful for policy analysis and infrastructure planning in both water and energy systems. In response, this paper developed an agent-based spatiotemporal integrated approach to simulate the water-energy consumption of each household or person agent in second throughout a whole day, considering the influences of out-of-home activities (e.g., work and shopping) on in-home activities (e.g., bathing, cooking and cleaning). The integrated approach was tested in the capital of China, Beijing. The temporal results suggested that the 24-hour distributions of water and related energy consumptions were quite similar, and the water-energy consumptions were highly correlated (with a Pearson correlation coefficient of 0.89); The spatial results suggested that people living in the central districts and the central areas of the outer districts tended to consume more water and related energy, and also the water-energy correlation varies across space. Such spatially and temporally explicit results are expected to be useful for policy making (e.g., time-of-use tariffs) and infrastructure planning and optimization in both water and energy sectors.
机译:住宅部门的水和能源消耗高度相关。更好地了解这种关系将有助于例如通过技术创新,管理和政策来节约用水和能源。最近,在水能源需求的分析和建模中,对更高时空分辨率的需求日益增长,因为其结果对于水和能源系统中的政策分析和基础设施规划将更加有用。作为回应,本文开发了一种基于代理的时空综合方法,以考虑到户外活动(例如工作和购物)的影响,在一天内模拟每个家庭或个人代理的水能耗。进行家庭活动(例如洗澡,做饭和打扫卫生)。集成方法已在中国首都北京进行了测试。时间结果表明,水和相关能源消耗的24小时分布非常相似,水能源消耗高度相关(皮尔森相关系数为0.89);空间结果表明,居住在中部地区和外围地区中部地区的人们倾向于消耗更多的水和相关能源,而且水与能源的相关性在空间上也有所不同。预期这种在空间和时间上明确的结果对于水和能源部门的政策制定(例如使用时间费率)以及基础设施规划和优化都是有用的。

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